neohsedu/toolcalling-merged-demo
TEXT GENERATIONConcurrency Cost:1Model Size:2BQuant:BF16Ctx Length:32kPublished:Apr 2, 2026License:apache-2.0Architecture:Transformer Open Weights Warm
The neohsedu/toolcalling-merged-demo is a 2 billion parameter Qwen3-based language model developed by neohsedu, fine-tuned for tool-calling capabilities. This model was efficiently trained using Unsloth and Huggingface's TRL library, enabling faster development. With a 32768 token context length, it is designed for applications requiring robust function calling and interaction with external tools.
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Model Overview
The neohsedu/toolcalling-merged-demo is a 2 billion parameter language model based on the Qwen3 architecture, developed by neohsedu. It has been specifically fine-tuned to excel in tool-calling scenarios, allowing it to interpret user requests and generate appropriate function calls for external tools or APIs.
Key Capabilities
- Tool Calling: Optimized for understanding and executing tool-use instructions, making it suitable for building agents or systems that interact with external functions.
- Efficient Training: This model was fine-tuned using Unsloth and Huggingface's TRL library, which facilitated a 2x faster training process compared to standard methods.
- Qwen3 Base: Leverages the robust architecture of the Qwen3 series, providing a strong foundation for language understanding and generation.
- Extended Context: Features a substantial context window of 32768 tokens, enabling it to handle complex multi-turn conversations and detailed tool specifications.
Good For
- Developing AI agents that require precise function calling.
- Integrating LLMs with external APIs and services.
- Applications demanding efficient and reliable tool-use capabilities.